CVE-2026-71211: Mlflow MLflow AI Gateway Permits SSRF Vulnerability

HIGH
Advisory Identifier: GHSA-h7x2-h6g9-p789
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CVSS 7.1
CWE-918
Published
Advisory Summary

CVE-2026-71211 is a HIGH (CVSS 7.1) mlflow ai gateway permits ssrf vulnerability (CWE-918: Server-Side Request Forgery (SSRF)) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow ai gateway permits ssrf through an unvalidated api_base. Remediation is available in the latest vendor maintenance releases.

CVE-2026-71211 at a Glance

CVE Identifier CVE-2026-71211
GHSA Identifier GHSA-h7x2-h6g9-p789
Severity HIGH
CVSS v3.1 Base Score 7.1
CWE Classification CWE-918: Server-Side Request Forgery (SSRF)
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.1

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required Low (PR:L)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity Low (I:L)
Availability None (A:N)

How to Fix CVE-2026-71211

To remediate this vulnerability, upgrade all affected Mlflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

mlflow fixed: Latest secure release 
pip install mlflow>=Latest secure release
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show mlflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-71211, inspect your installed packages using pip:

pip show mlflow

Analyze the terminal output to locate any version of Mlflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.

Note: The pip show mlflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-918: Server-Side Request Forgery (SSRF), where the web server receives a url or similar request from an upstream component and retrieves the contents of this url, but it does not sufficiently ensure that the request is being sent to the expected destination. In Mlflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

MLflow's AI Gateway accepts an auth_config.api_base value when creating a gateway secret (mlflow/server/handlers.py, _create_gateway_secret) with no validation of scheme, host, or IP range; the value is stored verbatim. The gateway proxy endpoint (mlflow/server/gateway_api.py, raw_proxy) subsequently issues an HTTP request to that stored api_base plus a caller-supplied path and returns the full response body. MLflow's existing SSRF guard, _validate_webhook_url (which blocks non-global and metadata IPs), is never invoked anywhere in this gateway secret/proxy code path. The CreateGatewaySecret action additionally has no entry in the permission-validator map, so it requires only basic authentication rather than any specific scope, meaning any authenticated user — including read-only accounts — can create a secret pointing at an internal address and reach it via the proxy endpoint, potentially exposing cloud-instance IAM credentials via metadata services. This is related to CVE-2026-4035, which addresses a distinct mechanism in the same gateway-secret feature (server-side $ENV_VAR resolution inside the api_key field leaking credentials to the configured upstream); the finding here is an independent missing-validation gap in the api_base destination itself, unaffected by that fix.

CVE-2026-71211 Affected Mlflow Versions

1 component(s)
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
≥ 3.13.0
≤ 3.15.2

References

NVD — CVE-2026-71211 NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-71211
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/96b7d900e14227e0821981409d86f5fb6c59b386
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow/tree/v3.14.0/mlflow

Frequently Asked Questions

What is CVE-2026-71211?
CVE-2026-71211 is a security vulnerability in Mlflow involving MLflow AI Gateway permits SSRF through an unvalidated api_base under CWE-918: Server-Side Request Forgery (SSRF).
Which Mlflow versions are affected?
Affected versions include releases prior to current release patches across affected packages: mlflow.
What version fixes CVE-2026-71211?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to Latest secure release. Upgrade your dependency to Latest secure release or later.
What is the CVSS score of CVE-2026-71211?
CVE-2026-71211 has a CVSS v3.1 base score of 7.1 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N.
What CWE is associated with CVE-2026-71211?
CVE-2026-71211 is classified under CWE-918: Server-Side Request Forgery (SSRF) (The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination.).
How can I check PyPI dependencies for CVE-2026-71211?
Run the dependency tree command: 'pip show mlflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-h7x2-h6g9-p789",
  "modified" : "2026-08-31T19:48:14Z",
  "published" : "2026-08-05T09:31:18Z",
  "aliases" : [ "CVE-2026-71211" ],
  "summary" : " MLflow AI Gateway permits SSRF through an unvalidated api_base",
  "details" : "MLflow's AI Gateway accepts an auth_config.api_base value when creating a gateway secret (mlflow/server/handlers.py, _create_gateway_secret) with no validation of scheme, host, or IP range; the value is stored verbatim. The gateway proxy endpoint (mlflow/server/gateway_api.py, raw_proxy) subsequently issues an HTTP request to that stored api_base plus a caller-supplied path and returns the full response body. MLflow's existing SSRF guard, _validate_webhook_url (which blocks non-global and metadata IPs), is never invoked anywhere in this gateway secret/proxy code path. The CreateGatewaySecret action additionally has no entry in the permission-validator map, so it requires only basic authentication rather than any specific scope, meaning any authenticated user — including read-only accounts — can create a secret pointing at an internal address and reach it via the proxy endpoint, potentially exposing cloud-instance IAM credentials via metadata services. This is related to CVE-2026-4035, which addresses a distinct mechanism in the same gateway-secret feature (server-side $ENV_VAR resolution inside the api_key field leaking credentials to the configured upstream); the finding here is an independent missing-validation gap in the api_base destination itself, unaffected by that fix.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "3.13.0"
      }, {
        "last_affected" : "3.15.2"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-71211"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/96b7d900e14227e0821981409d86f5fb6c59b386"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/tree/v3.14.0/mlflow"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-918" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-08-31T19:48:13Z",
    "nvd_published_at" : "2026-08-05T08:16:43Z"
  }
}